Improving Medical Image Classification Using Vision transformers

Abstract

The integration of Vision Transformers (ViTs) into the field of medical imaging has opened new avenues for accurate, data-driven diagnostics by leveraging self-attention mechanisms to capture global contextual information. in this project we explored the application of ViTs to various medical imaging tasks, including classification, segmentation, and anomaly detection in X-raysour project utilizes the Vision Transformer (ViT) deep learning technique to accurately classify medical images from a chest X-ray dataset, demonstrating its effectiveness in various fields like computer vision and medical applications.